Distinguishing pathophysiological features of heart failure with reduced and preserved ejection fraction: A comparative analysis of two mouse models.

Heart failure (HF) is a heterogeneous condition that can be categorized according to the left ventricular ejection fraction (EF) into HF with reduced (HFrEF) or preserved (HFpEF) EF. Although HFrEF and HFpEF share some common clinical manifestations, the mechanisms underlying each phenotype are often found to be distinct. Identifying shared and divergent pathophysiological features might expand our insights on HF pathophysiology and assist the search for therapies for each HF subtype. In this study, we evaluated and contrasted two new murine models of non-ischaemic HFrEF and cardiometabolic HFpEF in terms of myocardial structure, left ventricular function, gene expression, cardiomyocyte calcium handling, mitochondrial polarization and protein acetylation in a head-to-head fashion. We found that in conditions of similar haemodynamic stress, the HFrEF myocardium underwent a more pronounced hypertrophic and fibrotic remodelling, whereas inflammation was greater in the HFpEF myocardium. We observed opposing features on calcium release, which was diminished in the HFrEF cardiomyocyte but enhanced in the HFpEF cardiomyocyte. Mitochondria were less polarized in both HFrEF and HFpEF cardiomyocytes, reflecting similarly impaired metabolic capacity. Hyperacetylation of cardiac proteins was observed in both models, but it was more accentuated in the HFpEF heart. Despite shared features, unique triggering mechanisms (neurohormonal overactivation in HFrEF vs. inflammation in HFpEF) appear to determine the distinct phenotypes of HF. The findings of the present research stress the need for further exploration of the differential mechanisms underlying each HF subtype, because they might require specific therapeutic interventions. KEY POINTS: The mechanisms underlying heart failure with either reduced (HFrEF) or preserved (HFpEF) ejection fraction are often found to be different. Previous studies comparing pathophysiological traits between HFrEF and HFpEF have been conducted on animals of different ages and strains. The present research contrasted two age-matched mouse models of non-ischaemic HFrEF and cardiometabolic HFpEF to uncover divergent and shared features. We found that upon similar haemodynamic stress, the HFrEF heart experienced a more pronounced hypertrophic and fibrotic remodelling, whereas inflammation appeared to be greater in the HFpEF myocardium. Calcium release was diminished in the HFrEF cardiomyocyte and enhanced in the HFpEF cardiomyocyte. Mitochondria were comparably less polarized in both HFrEF and HFpEF myocytes. Hyperacetylation of proteins was common to both models, but stronger in the HFpEF heart. Casting light on common and distinguishing features might ease the quest for phenotype-specific therapies for heart failure patients.

MuTATE-an R package for comprehensive multi-objective molecular modeling.

MOTIVATION: Comprehensive multi-omics studies have driven advances in disease modeling for effective precision medicine but pose a challenge for existing machine-learning approaches, which have limited interpretability across clinical endpoints. Automated, comprehensive disease modeling requires a machine-learning approach that can simultaneously identify disease subgroups and their defining molecular biomarkers by explaining multiple clinical endpoints. Current tools are restricted to individual endpoints or limited variable types, necessitate advanced computation skills, and require resource-intensive manual expert interpretation. RESULTS: We developed Multi-Target Automated Tree Engine (MuTATE) for automated and comprehensive molecular modeling, which enables user-friendly multi-objective decision tree construction and visualization of relationships between molecular biomarkers and patient subgroups characterized by multiple clinical endpoints. MuTATE incorporates multiple targets throughout model construction and allows for target weights, enabling construction of interpretable decision trees that provide insights into disease heterogeneity and molecular signatures. MuTATE eliminates the need for manual synthesis of multiple non-explainable models, making it highly efficient and accessible for bioinformaticians and clinicians. The flexibility and versatility of MuTATE make it applicable to a wide range of complex diseases, including cancer, where it can improve therapeutic decisions by providing comprehensive molecular insights for precision medicine. MuTATE has the potential to transform biomarker discovery and subtype identification, leading to more effective and personalized treatment strategies in precision medicine, and advancing our understanding of disease mechanisms at the molecular level. AVAILABILITY AND IMPLEMENTATION: MuTATE is freely available at GitHub (https://github.com/SarahAyton/MuTATE) under the GPLv3 license.

The retinoic acid response is a minor component of the cardiac phenotype in H9c2 myoblast differentiation.

The H9c2 myoblast cell line, isolated from the left ventricular tissue of rat, is currently used in vitro as a mimetic for skeletal and cardiac muscle due to its biochemical, morphological, and electrical/hormonal signaling properties. During culture, H9c2 cells acquire a myotube phenotype, where a critical component is the inclusion of retinoic acid (RA). The results from some authors on H9c2 suggested that thousands of genes respond to RA stimuli, while others report hundreds of genes responding to RA over different cell types. In this article, using a more appropriate experimental design, we first confirm the H9c2 cardiac phenotype with and without RA and report transcriptomic and physiological changes regarding calcium handling, bioenergetics, and other biological concepts. Interestingly, of the 2360 genes showing a transcriptional change, 622 genes were statistically associated with the RA response. Of these genes, only 305 were RA-specific, and the rest also showed a culture-time component. Thus, the major expression changes (from 74 to 87%) were indeed due to culture conditions over time. Unexpectedly, only a few components of the retinol pathway in KEGG responded to RA. Our results show the role of RA in the H9c2 cultures impacting the interpretation using H9c2 as an in vitro model.

A systematic review and functional bioinformatics analysis of genes associated with Crohn's disease identify more than 120 related genes.

BACKGROUND: Crohn's disease is one of the two categories of inflammatory bowel diseases that affect the gastrointestinal tract. The heritability estimate has been reported to be 0.75. Several genes linked to Crohn's disease risk have been identified using a plethora of strategies such as linkage-based studies, candidate gene association studies, and lately through genome-wide association studies (GWAS). Nevertheless, to our knowledge, a compendium of all the genes that have been associated with CD is lacking. METHODS: We conducted functional analyses of a gene set generated from a systematic review where genes potentially related to CD found in the literature were analyzed and classified depending on the genetic evidence reported and putative biological function. For this, we retrieved and analyzed 2496 abstracts comprising 1067 human genes plus 22 publications regarding 133 genes from GWAS Catalog. Then, each gene was curated and categorized according to the type of evidence associated with Crohn's disease. RESULTS: We identified 126 genes associated with Crohn's disease risk by specific experiments. Additionally, 71 genes were recognized associated through GWAS alone, 18 to treatment response, 41 to disease complications, and 81 to related diseases. Bioinformatic analysis of the 126 genes supports their importance in Crohn's disease and highlights genes associated with specific aspects such as symptoms, drugs, and comorbidities. Importantly, most genes were not included in commercial genetic panels suggesting that Crohn's disease is genetically underdiagnosed. CONCLUSIONS: We identified a total of 126 genes from PubMed and 71 from GWAS that showed evidence of association to diagnosis, 18 to treatment response, and 41 to disease complications in Crohn's disease. This prioritized gene catalog can be explored at http://victortrevino.bioinformatics.mx/CrohnDisease .

Multiomics subtyping for clinically prognostic cancer subtypes and personalized therapy: A systematic review and meta-analysis.

PURPOSE: Multiomics cancer subtyping is becoming increasingly popular for directing state-of-the-art therapeutics. However, these methods have never been systematically assessed for their ability to capture cancer prognosis for identified subtypes, which is essential to effectively treat patients. METHODS: We systematically searched PubMed, The Cancer Genome Atlas, and Pan-Cancer Atlas for multiomics cancer subtyping studies from 2010 through 2019. Studies comprising at least 50 patients and examining survival were included. Pooled Cox and logistic mixed-effects models were used to compare the ability of multiomics subtyping methods to identify clinically prognostic subtypes, and a structural equation model was used to examine causal paths underlying subtyping method and mortality. RESULTS: A total of 31 studies comprising 10,848 unique patients across 32 cancers were analyzed. Latent-variable subtyping was significantly associated with overall survival (adjusted hazard ratio, 2.81; 95% CI, 1.16-6.83; P = .023) and vital status (1 year adjusted odds ratio, 4.71; 95% CI, 1.34-16.49; P = .015; 5 year adjusted odds ratio, 7.69; 95% CI, 1.83-32.29; P = .005); latent-variable-identified subtypes had greater associations with mortality across models (adjusted hazard ratio, 1.19; 95% CI, 1.01-1.42; P = .050). Our structural equation model confirmed the path from subtyping method through multiomics subtype (߈ = 0.66; P = .048) on survival (߈ = 0.37; P = .008). CONCLUSION: Multiomics methods have different abilities to define clinically prognostic cancer subtypes, which should be considered before administration of personalized therapy; preliminary evidence suggests that latent-variable methods better identify clinically prognostic biomarkers and subtypes.

Plasma and vacuolar membrane sphingolipidomes: composition and insights on the role of main molecular species.

Lipid structures affect membrane biophysical properties such as thickness, stability, permeability, curvature, fluidity, asymmetry, and interdigitation, contributing to membrane function. Sphingolipids are abundant in plant endomembranes and plasma membranes (PMs) and comprise four classes: ceramides, hydroxyceramides, glucosylceramides, and glycosylinositolphosphoceramides (GIPCs). They constitute an array of chemical structures whose distribution in plant membranes is unknown. With the aim of describing the hydrophobic portion of sphingolipids, 18 preparations from microsomal (MIC), vacuolar (VM), PM, and detergent-resistant membranes (DRM) were isolated from Arabidopsis (Arabidopsis thaliana) leaves. Sphingolipid species, encompassing pairing of long-chain bases and fatty acids, were identified and quantified in these membranes. Sphingolipid concentrations were compared using univariate and multivariate analysis to assess sphingolipid diversity, abundance, and predominance across membranes. The four sphingolipid classes were present at different levels in each membrane: VM was enriched in glucosylceramides, hydroxyceramides, and GIPCs; PM in GIPCs, in agreement with their key role in signal recognition and sensing; and DRM in GIPCs, as reported by their function in nanodomain formation. While a total of 84 sphingolipid species was identified in MIC, VM, PM, and DRM, only 34 were selectively distributed in the four membrane types. Conversely, every membrane contained a different number of predominant species (11 in VM, 6 in PM, and 17 in DRM). This study reveals that MIC, VM, PM, and DRM contain the same set of sphingolipid species but every membrane source contains its own specific assortment based on the proportion of sphingolipid classes and on the predominance of individual species.

Generating human papillomavirus (HPV) reference databases to maximize genomic mapping.

Genomic experiments analyzing human papillomaviruses (HPVs) require a carefully selected list of sequences as a reference database to map millions of reads. The available sources, such as the Papillomavirus Episteme (PaVE), are organized based on variations in the L1 gene rather than the whole HPV sequence. Moreover, the PaVE process uses complex multiple sequence alignments containing hundreds or thousands of sequences. These issues complicate the generation of a reference database for genomics, leading to the generation of per-analysis-defined databases. Here, we propose a de novo strategy considering all HPV sequences reported in the NCBI database to define a subset of highly representative HPV sequences. The strategy is based on oligonucleotide frequency profiling of the whole sequence followed by hierarchical clustering. Using data from HPV capture experiments, we demonstrate that this strategy selects suitable sequences as a reference database to map most mappable reads unambiguously. We provide some recommendations to improve HPV mapping. The generated .fasta files can be accessed at https://github.com/vtrevino/HPV-Ref-Genomes .

Analysis of HPV Integrations in Mexican Pre-Tumoral Cervical Lesions Reveal Centromere-Enriched Breakpoints and Abundant Unspecific HPV Regions.

Human papillomavirus (HPV) DNA integration is a crucial event in cervical carcinogenesis. However, scarce studies have focused on studying HPV integration (HPVint) in early-stage cervical lesions. Using HPV capture followed by sequencing, we investigated HPVint in pre-tumor cervical lesions. Employing a novel pipeline, we analyzed reads containing direct evidence of the integration breakpoint. We observed multiple HPV infections in most of the samples (92%) with a median integration rate of 0.06% relative to HPV mapped reads corresponding to two or more sequence breakages. Unlike cancer studies, most integrations events were unique (supported by one read), consistent with the lack of clonal selection. Congruent to other studies, we found that breakpoints could occur, practically, in any part of the viral genome. We noted that L1 had a higher frequency of rupture integration (25%). Based on host genome integration frequencies, we found previously reported integration sites in cancer for genes like FHIT, CSMD1, and LRP1B and putatively many new ones such as those exemplified in CSMD3, ROBO2, and SETD3. Similar host integrations regions and genes were observed in diverse HPV types within many genes and even equivalent integration positions in different samples and HPV types. Interestingly, we noted an enrichment of integrations in most centromeres, suggesting a possible mechanism where HPV exploits this structural machinery to facilitate integration. Supported by previous findings, overall, our analysis provides novel information and insights about HPVint.

Transcriptomic and cellular analyses of CRISPR/Cas9-mediated edition of FASN show inhibition of aggressive characteristics in breast cancer cells.

Several genes are significantly mutated in breast cancer but only a small percentage of mutations are well-known to contribute to cancer development. FASN is involved in de novo lipogenesis and the regulation of ERα signaling. However, the effect of genetic mutations affecting FASN in breast cancer has not thoroughly studied. Therefore, we used the CRISPR/Cas9 system to edit the FASN locus in MCF-7 cells and evaluated its biological effect. We obtained four clones carrying mutations and frameshifts in the acyl-transferase domain of FASN. We found that clones had reduced proliferation, migration, viability, and showed alterations in cell cycle profiles. RNA-Seq analysis demonstrates that a lack of fully functional FASN may have a more significant role in proliferation-related genes than in lipid metabolism. We conclude that functional knockouts in FASN contributes to decrease the proliferation and migration of breast cancer cells contrary to point mutations in breast cancer patients.

Landscape of genomic alterations in cervical carcinomas.

Cervical cancer is responsible for 10-15% of cancer-related deaths in women worldwide. The aetiological role of infection with high-risk human papilloma viruses (HPVs) in cervical carcinomas is well established. Previous studies have also implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as several copy-number alterations in the pathogenesis of cervical carcinomas. Here we report whole-exome sequencing analysis of 115 cervical carcinoma-normal paired samples, transcriptome sequencing of 79 cases and whole-genome sequencing of 14 tumour-normal pairs. Previously unknown somatic mutations in 79 primary squamous cell carcinomas include recurrent E322K substitutions in the MAPK1 gene (8%), inactivating mutations in the HLA-B gene (9%), and mutations in EP300 (16%), FBXW7 (15%), NFE2L2 (4%), TP53 (5%) and ERBB2 (6%). We also observe somatic ELF3 (13%) and CBFB (8%) mutations in 24 adenocarcinomas. Squamous cell carcinomas have higher frequencies of somatic nucleotide substitutions occurring at cytosines preceded by thymines (Tp*C sites) than adenocarcinomas. Gene expression levels at HPV integration sites were statistically significantly higher in tumours with HPV integration compared with expression of the same genes in tumours without viral integration at the same site. These data demonstrate several recurrent genomic alterations in cervical carcinomas that suggest new strategies to combat this disease.

Arresting proliferation improves the cell identity of corneal endothelial cells in the New Zealand rabbit.

Purpose: Corneal endothelium engineering aims to reduce the tissue shortage for corneal grafts. We investigated the impact of mitogenic and resting culture systems on the identity of corneal endothelial cells (CECs) for tissue engineering purposes. Methods: Rabbit CECs were cultured in growth factor-supplemented media (MitoM) until confluence. At the first passage, the CECs were divided into two populations: P1 remained cultured in MitoM, and P2 was cultured in a basal medium (RestM) for another passage. Morphologic changes in the CECs were analyzed, and RNA was isolated for transcriptome analysis. Quantitative PCR and immunocytochemistry validation of selected differentially expressed markers were performed. Results: The CECs in MitoM showed fibroblastic morphology, whereas the CECs in RestM exhibited polygonal morphology. Circularity analysis showed similar values in human (0.75±0.056), rabbit basal (before cultured; 0.77±0.063), and CECs in RestM (0.73±0.09), while MitoM showed lower circularities (0.41±0.19). Genes related to collagen type IV and the extracellular matrix, along with the adult CEC markers ATP1A1, ATP1B1, COL8A2, GPC4, and TJP1, were highly expressed in RestM. Conversely, the IL-6, F3, and ITGB3 genes and the non-adult CEC markers CD44, CNTN3, and CD166 were more expressed in MitoM. Overall, from the transcriptome, we identified 832 differentially expressed probes. A functional analysis of the 308 human annotated differentially expressed genes revealed around 13 functional clusters related to important biological terms, such as extracellular matrix, collagen type 4, immune responses, cell proliferation, and wound healing. Quantitative PCR and immunocytochemistry confirmed the overexpression of ATP1A1, TJP1, and GPC4 in CECs in RestM. Conclusions: The addition of a stabilization step during CEC culture improves the cells' morphology and molecular identity, which agrees with transcriptome data. This suggests that stabilization is useful for studying the plasticity of the corneal endothelium's morphology, and stabilization is proposed as a necessary step in corneal endothelium engineering.

VALORATE: fast and accurate log-rank test in balanced and unbalanced comparisons of survival curves and cancer genomics.

SUMMARY: The association of genomic alterations to outcomes in cancer is affected by a problem of unbalanced groups generated by the low frequency of alterations. For this, an R package (VALORATE) that estimates the null distribution and the P -value of the log-rank based on a recent reformulation is presented. For a given number of alterations that define the size of survival groups, the log-rank density is estimated by a weighted sum of conditional distributions depending on a co-occurrence term of mutations and events. The estimations are accurately accelerated by sampling across co-occurrences allowing the analysis of large genomic datasets in few minutes. In conclusion, the proposed VALORATE R package is a valuable tool for survival analysis. AVAILABILITY AND IMPLEMENTATION: The R package is available in CRAN at https://cran.r-project.org and in http://bioinformatica.mty.itesm.mx/valorateR . CONTACT: vtrevino@itesm.mx. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A New Gene Expression Signature for Triple Negative Breast Cancer Using Frozen Fresh Tissue before Neoadjuvant Chemotherapy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer tumors. Comparisons between TNBC and non-triple negative breast cancer (nTNBC) may help to differentiate key components involved in TNBC neoplasms. The purpose of the study was to analyze the expression profile of TNBC versus nTNBC tumors in a homogeneous population from northeastern Mexico. A prospective study of 50 patients was conducted (25 TNBC and 25 nTNBC). Clinic parameters were equally distributed for TNBC and nTNBC: age at diagnosis (51 vs 47 years, p=0.1), glucose levels (107 mg/dl vs 104 mg/dl, p=0.64), and body mass index (28 vs 29, p=0.14), respectively. Core biopsies were collected for histopathological diagnosis and gene expression analyses. Total RNA was isolated and expression profiling was performed. 40 genes showed differential expression pattern in TNBC tumors. Among these, 9 over-expressed genes (PRKX/PRKY, UGT8, HMGA1, LPIN1, HAPLN3, and ANKRD11), and one under-expressed (ANX9) gene are involved in general metabolism. Based on this biochemical peculiarity, and the over-expression of BCL11A and FOXC1 (involved in tumor growth and metastasis, respectively) we validated by qPCR the expression profile of 7 genes out of the signature. In this report, a new gene signature for TNBC is proposed. To our knowledge, this is the first TNBC signature which describes genes involved in general metabolism. The findings may be pertinent for Mexican patients and require to be evaluated in further ethnic groups and populations.

Integrated transcriptomic and metabolomic analysis shows that disturbances in metabolism of tumor cells contribute to poor survival of RCC patients.

PURPOSE: Cellular metabolism of renal cell carcinoma (RCC) tumors is disturbed. The clinical significance of these alterations is weakly understood. We aimed to find if changes in metabolic pathways contribute to survival of RCC patients. MATERIAL AND METHODS: 35 RCC tumors and matched controls were used for metabolite profiling using gas chromatography-mass spectrometry and transcriptomic analysis with qPCR-arrays targeting the expression of 93 metabolic genes. The clinical significance of obtained data was validated on independent cohort of 468 RCC patients with median follow-up of 43.22months. RESULTS: The levels of 31 metabolites were statistically significantly changed in RCC tumors compared with controls. The top altered metabolites included beta-alanine (+4.2-fold), glucose (+3.4-fold), succinate (-11.0-fold), myo-inositol (-4.6-fold), adenine (-4.2-fold), uracil (-3.7-fold), and hypoxanthine (-3.0-fold). These disturbances were associated with altered expression of 53 metabolic genes. ROC curve analysis revealed that the top metabolites discriminating between tumor and control samples included succinate (AUC=0.91), adenine (AUC=0.89), myo-inositol (AUC=0.87), hypoxanthine (AUC=0.85), urea (AUC=0.85), and beta-alanine (AUC=0.85). Poor survival of RCC patients correlated (p<0.0001) with altered expression of genes involved in metabolism of succinate (HR=2.7), purines (HR=2.4), glucose (HR=2.4), beta-alanine (HR=2.5), and myo-inositol (HR=1.9). CONCLUSIONS: We found that changes in metabolism of succinate, beta-alanine, purines, glucose and myo-inositol correlate with poor survival of RCC patients.

Avocado fruit maturation and ripening: dynamics of aliphatic acetogenins and lipidomic profiles from mesocarp, idioblasts and seed.

BACKGROUND: Avocado fruit contains aliphatic acetogenins (oft-acetylated, odd-chain fatty alcohols) with promising bioactivities for both medical and food industries. However, we have scarce knowledge about their metabolism. The present work aimed to study changes in acetogenin profiles from mesocarp, lipid-containing idioblasts, and seeds from 'Hass' cultivar during fruit development, germination, and three harvesting years. An untargeted LC-MS based lipidomic analysis was also conducted to profile the lipidome of avocado fruit in each tissue. RESULTS: The targeted analysis showed that acetogenin profiles and contents remained unchanged in avocado mesocarp during maturation and postharvest ripening, germination, and different harvesting years. However, a shift in the acetogenin profile distribution, accompanied with a sharp increase in concentration, was observed in seed during early maturation. Untargeted lipidomics showed that this shift was accompanied with remodeling of glycerolipids: TAGs and DAGs decreased during fruit growing in seed. Remarkably, the majority of the lipidome in mature seed was composed by acetogenins; we suggest that this tissue is able to synthesize them independently from mesocarp. On the other hand, lipid-containing idioblasts accumulated almost the entire acetogenin pool measured in the whole mesocarp, while only having 4% of the total fatty acids. The lipidome of this cell type changed the most when the fruit was ripening after harvesting, TAGs decreased while odd-chain DAGs increased. Notably, idioblast lipidome was more diverse than that from mesocarp. CONCLUSIONS: Evidence shown here suggests that idioblasts are the main site of acetogenin biosynthesis in avocado mesocarp. This work unveiled the prevalence of aliphatic acetogenins in the avocado fruit lipidome and evidenced TAGs as initial donors of the acetogenin backbones in its biosynthesis. It also sets evidence for acetogenins being included in future works aimed at characterizing the avocado seed, as they are a main component of their lipidome.

A systematic review of genetic mutations in pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a group of vascular diseases that produce right ventricular dysfunction, heart failure syndrome, and death. Although the majority of patients appear idiopathic, accumulated research work combined with current sequencing technology show that many gene variants could be an important component of the disease. However, current guidelines, clinical practices, and available gene panels focus the diagnosis of PAH on a relatively low number of genes and variants associated with the bone morphogenic proteins and transforming Growth Factor-ß pathways, such as the BMPR2, ACVRL1, CAV1, ENG, and SMAD9. METHODS: To provide an expanded view of the genes and variants associated with PAH, we performed a systematic literature review. Facilitated by a web tool, we classified, curated, and annotated most of the genes and PubMed abstracts related to PAH, in which many of the mutations and variants were not annotated in public databases such as ClinVar from NCBI. The gene list generated was compared with other available tests. RESULTS: Our results reveal that there is genetic evidence for at least 30 genes, of which 21 genes shown specific mutations. Most of the genes are not covered by current available genetic panels. Many of these variants were not annotated in the ClinVar database and a mapping of these mutations suggest that next generation sequencing is needed to cover all mutations found in PAH or related diseases. A pathway analysis of these genes indicated that, in addition to the BMP and TGFß pathways, there was connections with the nitric oxide, prostaglandin, and calcium homeostasis signalling, which may be important components in PAH. CONCLUSION: Our systematic review proposes an expanded gene panel for more accurate characterization of the genetic incidence and risk in PAH. Their usage would increase the knowledge of PAH in terms of genetic counseling, early diagnosis, and potential prognosis of the disease.

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems.

Entrainment of Breast Cell Lines Results in Rhythmic Fluctuations of MicroRNAs.

Circadian rhythms are essential for temporal (~24 h) regulation of molecular processes in diverse species. Dysregulation of circadian gene expression has been implicated in the pathogenesis of various disorders, including hypertension, diabetes, depression, and cancer. Recently, microRNAs (miRNAs) have been identified as critical modulators of gene expression post-transcriptionally, and perhaps involved in circadian clock architecture or their output functions. The aim of the present study is to explore the temporal expression of miRNAs among entrained breast cell lines. For this purpose, we evaluated the temporal (28 h) expression of 2006 miRNAs in MCF-10A, MCF-7, and MDA-MB-231 cells using microarrays after serum shock entrainment. We noted hundreds of miRNAs that exhibit rhythmic fluctuations in each breast cell line, and some of them across two or three cell lines. Afterwards, we validated the rhythmic profiles exhibited by miR-141-5p, miR-1225-5p, miR-17-5p, miR-222-5p, miR-769-3p, and miR-548ay-3p in the above cell lines, as well as in ZR-7530 and HCC-1954 using RT-qPCR. Our results show that serum shock entrainment in breast cells lines induces rhythmic fluctuations of distinct sets of miRNAs, which have the potential to be related to endogenous circadian clock, but extensive investigation is required to elucidate that connection.

SurvMicro: assessment of miRNA-based prognostic signatures for cancer clinical outcomes by multivariate survival analysis.

UNLABELLED: MicroRNAs (miRNAs) play a key role in post-transcriptional regulation of mRNA levels. Their function in cancer has been studied by high-throughput methods generating valuable sources of public information. Thus, miRNA signatures predicting cancer clinical outcomes are emerging. An important step to propose miRNA-based biomarkers before clinical validation is their evaluation in independent cohorts. Although it can be carried out using public data, such task is time-consuming and requires a specialized analysis. Therefore, to aid and simplify the evaluation of prognostic miRNA signatures in cancer, we developed SurvMicro, a free and easy-to-use web tool that assesses miRNA signatures from publicly available miRNA profiles using multivariate survival analysis. SurvMicro is composed of a wide and updated database of >40 cohorts in different tissues and a web tool where survival analysis can be done in minutes. We presented evaluations to portray the straightforward functionality of SurvMicro in liver and lung cancer. To our knowledge, SurvMicro is the only bioinformatic tool that aids the evaluation of multivariate prognostic miRNA signatures in cancer. AVAILABILITY AND IMPLEMENTATION: SurvMicro and its tutorial are freely available at http://bioinformatica.mty.itesm.mx/SurvMicro.